GPU-cluster quantum simulation

Enabling Quantum Workloads on National Supercomputers

As quantum algorithms increase in scale and complexity, validating them requires HPC-level compute power.

Through collaboration with CINECA’s Leonardo pre-exascale supercomputer, Classiq demonstrated scalable, multi-GPU-accelerated quantum simulation of real industry workloads.

What Classiq Enabled on Leonardo

• High-level quantum modeling using Classiq
• Automatic synthesis of optimized circuits
• Reduced circuit depth via integration-based exponential amplitude loading
• Containerized simulator deployment on HPC
• NVIDIA GPU acceleration
• Multi-node, multi-GPU simulation
• Successful execution of 30+ qubit financial circuits

This transformed Leonardo into a quantum-ready simulation platform.

Industry-Grade Use Case: Autocallable Option Pricing

Using Classiq’s modeling platform, researchers implemented and simulated a complex path-dependent autocallable derivative pricing algorithm.

The workflow:

Quantum modeling → Circuit optimization → multi-GPU-accelerated HPC simulation → Classical validation

The results validated both:

• The efficiency of Classiq’s circuit synthesis
• The scalability of Leonardo for large quantum simulations

This demonstrates that enterprise-relevant quantum workloads can already leverage national HPC infrastructure today.

Strategic Value for HPC Organizations

Classiq enables supercomputing centers to:

• Attract high-value quantum research and industry collaborations
• Increase GPU cluster utilization with next-generation workloads
• Position themselves at the forefront of quantum-HPC convergence
• Support financial institutions and advanced R&D initiatives
  

Quantum computing will augment HPC — not replace it.

Classiq provides the software layer that makes that convergence scalable and practical.